Diaptomid Thermal Limits

Site Map

coords = site_data %>%
  dplyr::select(site, long, lat, collection_temp) %>%
  drop_na(collection_temp) %>% 
  distinct()

map_data("world") %>% 
  filter(region %in% c("USA", "Canada")) %>% 
  ggplot() + 
  geom_polygon(aes(x = long, y = lat, group = group),
               fill = "lightgrey") + 
  coord_map(xlim = c(-110,-60),
            ylim = c(25, 55)) + 
  geom_point(data = coords,
             mapping = aes(x = long, y = lat, colour = collection_temp),
             size = 3) +
  scale_colour_viridis_c(option = "F") + 
  labs(x = "Longitude", 
       y = "Latitude",
       colour = "Temp.") + 
  theme_matt() + 
  theme(legend.position = "right")

CTmax Data

ctmax_temp_plot = ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = collection_temp, y = ctmax)) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point(aes(colour = species)) + 
  labs(x = "Collection Temp. (°C)", 
       y = "CTmax (°C)") + 
  scale_colour_manual(values = skisto_cols) + 
  theme_matt() + 
  theme(legend.position = "right")

ctmax_lat_plot = ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = lat, y = ctmax)) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point(aes(colour = species)) + 
  labs(x = "Latitude", 
       y = "CTmax (°C)") + 
  scale_colour_manual(values = skisto_cols) + 
  theme_matt() + 
  theme(legend.position = "right")

ctmax_elev_plot = ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = elevation, y = ctmax)) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point(aes(colour = species)) +
  labs(x = "Elevation (m)", 
       y = "CTmax (°C)") +
  scale_colour_manual(values = skisto_cols) + 
  theme_matt() + 
  theme(legend.position = "right")

ggpubr::ggarrange(ctmax_temp_plot, ctmax_lat_plot, ctmax_elev_plot, common.legend = T, legend = "right", nrow = 1)

ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = collection_temp, y = ctmax)) + 
  facet_wrap(species~.) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point() + 
  labs(x = "Collection Temp. (°C)",
       y = "CTmax (°C)") + 
  theme_matt() + 
  theme(legend.position = "none")

ctmax_data %>% 
  filter(str_detect(species, pattern = "skisto") | 
           str_detect(species, pattern = "lepto")) %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  group_by(collection_date, species, collection_temp) %>% 
  summarise(mean_ctmax = mean(ctmax),
            ctmax_sd = sd(ctmax),
            ctmax_n = n(), 
            ctmax_se = ctmax_sd / sqrt(ctmax_n)) %>% 
  ggplot(aes(x = collection_temp, y = mean_ctmax, colour = species)) + 
  geom_smooth(method = "lm", se=F, linewidth = 2) + 
  geom_point(size = 2) + 
  geom_errorbar(aes(ymin = mean_ctmax - ctmax_se, 
                    ymax = mean_ctmax + ctmax_se),
                width = 0.3, linewidth = 1) + 
  labs(x = "Collection Temp. (°C)",
       y = "CTmax (°C)") + 
  scale_colour_manual(values = skisto_cols) + 
  theme_matt() + 
  theme(legend.position = "right")

ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = collection_temp, y = size)) + 
  facet_wrap(species~.) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point() + 
  labs(x = "Collection Temp. (°C)",
       y = "Prosome Length (mm)") + 
  theme_matt() + 
  theme(legend.position = "none")

ctmax_data %>% 
  mutate(species = str_replace(species, "_", " "),
         species = str_to_sentence(species)) %>% 
  ggplot(aes(x = collection_temp, y = mean_egg)) + 
  facet_wrap(species~.) + 
  geom_smooth(method = "lm", colour = "black") + 
  geom_point() + 
  labs(x = "Collection Temp. (°C)",
       y = "Prosome Length (mm)") + 
  theme_matt() + 
  theme(legend.position = "none")

ctmax_data %>% 
  select(elevation, collection_temp) %>% 
  distinct() %>% 
  ggplot(aes(x = elevation, y = collection_temp)) + 
  geom_point(size = 3) +
  labs(x = "Elevation (m)", 
       y = "Collection Temp. (°C)") + 
  theme_matt()

ggplot(ctmax_data, aes(x = size, y = ctmax, colour = species)) + 
  facet_wrap(.~species) + 
  geom_point() + 
  theme_matt() + 
  theme(legend.position = "none")

ggplot(ctmax_data, aes(x = size, y = total_egg_volume)) + 
  geom_smooth(method = "lm", formula = y ~ exp(x)) + 
  geom_point()+
  labs(x = "Prosome Length (mm)",
       y = "Total Egg Volume (mm^3)") + 
  theme_matt()

ggplot(ctmax_data, aes(x = size, y = total_egg_volume)) + 
  facet_wrap(.~species) + 
  geom_point()+
  #geom_smooth() + 
  labs(x = "Prosome Length (mm)",
       y = "Total Egg Volume (mm^3)") + 
  theme_matt()

model_data = ctmax_data %>% 
  mutate("genus" = str_split_fixed(species, pattern = "_", n = 2)[,1],
         genus = tools::toTitleCase(genus),
         "doy" = yday(collection_date)) %>% 
  select(site, collection_date, doy, collection_temp, lat, elevation, species, genus, sample_id, fecundity, size, ctmax) %>% 
  filter(genus != "MH")

ctmax_temp.model = lm(data = model_data, 
                      ctmax ~ genus + collection_temp + lat + elevation)

ctmax_resids = residuals(ctmax_temp.model)

performance::check_model(ctmax_temp.model)
## Package `see` required for model diagnostic plots.
##   There are binary versions available but the source versions are later:
##             binary source needs_compilation
## correlation  0.8.4  0.8.5             FALSE
## effectsize   0.8.6  0.8.9             FALSE
## modelbased   0.8.6  0.8.8             FALSE
## parameters  0.21.2 0.22.2             FALSE
## see          0.8.0  0.9.0             FALSE
## 
## $VIF
## # Check for Multicollinearity
## 
## $QQ
##            x            y
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## 152 34.75347 -3.150074640
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## 
## $NORM
##             x          y       curve
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## 2   -2.428775 0.02150828 0.002854642
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## 150 -1.840039 0.03586569 0.026453538
## 151 -1.836061 0.03628777 0.026798468
## 152 -1.832083 0.03672275 0.027147133
## 153 -1.828105 0.03716720 0.027499564
## 154 -1.824127 0.03762118 0.027855789
## 155 -1.820149 0.03809166 0.028215838
## 156 -1.816172 0.03857228 0.028579739
## 157 -1.812194 0.03906304 0.028947522
## 158 -1.808216 0.03956795 0.029319216
## 159 -1.804238 0.04008676 0.029694849
## 160 -1.800260 0.04061627 0.030074452
## 161 -1.796282 0.04115726 0.030458054
## 162 -1.792304 0.04171616 0.030845684
## 163 -1.788326 0.04228628 0.031237371
## 164 -1.784348 0.04286767 0.031633145
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## 171 -1.756502 0.04734426 0.034520471
## 172 -1.752524 0.04804315 0.034950002
## 173 -1.748546 0.04875648 0.035383885
## 174 -1.744568 0.04948218 0.035822150
## 175 -1.740591 0.05022291 0.036264827
## 176 -1.736613 0.05098210 0.036711945
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## 179 -1.724679 0.05334215 0.038080240
## 180 -1.720701 0.05416004 0.038545417
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## 182 -1.712745 0.05583683 0.039489567
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## 184 -1.704789 0.05757687 0.040452307
## 185 -1.700811 0.05846537 0.040940721
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## 188 -1.688877 0.06122838 0.042434492
## 189 -1.684899 0.06217756 0.042942023
## 190 -1.680921 0.06314224 0.043454406
## 191 -1.676943 0.06411839 0.043971669
## 192 -1.672965 0.06510648 0.044493842
## 193 -1.668987 0.06611279 0.045020954
## 194 -1.665010 0.06712992 0.045553033
## 195 -1.661032 0.06815774 0.046090109
## 196 -1.657054 0.06920051 0.046632209
## 197 -1.653076 0.07025597 0.047179362
## 198 -1.649098 0.07132127 0.047731597
## 199 -1.645120 0.07239741 0.048288943
## 200 -1.641142 0.07348802 0.048851426
## 201 -1.637164 0.07458744 0.049419076
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## 204 -1.625230 0.07794565 0.051153303
## 205 -1.621252 0.07908273 0.051741897
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## 207 -1.613296 0.08138382 0.052935029
## 208 -1.609318 0.08254533 0.053539621
## 209 -1.605340 0.08371272 0.054149601
## 210 -1.601362 0.08488847 0.054764994
## 211 -1.597384 0.08606937 0.055385828
## 212 -1.593406 0.08725460 0.056012130
## 213 -1.589429 0.08844483 0.056643926
## 214 -1.585451 0.08963962 0.057281242
## 215 -1.581473 0.09083709 0.057924105
## 216 -1.577495 0.09203701 0.058572540
## 217 -1.573517 0.09323975 0.059226574
## 218 -1.569539 0.09444347 0.059886232
## 219 -1.565561 0.09564786 0.060551539
## 220 -1.561583 0.09685245 0.061222521
## 221 -1.557605 0.09805614 0.061899203
## 222 -1.553627 0.09925864 0.062581610
## 223 -1.549649 0.10045961 0.063269765
## 224 -1.545671 0.10165675 0.063963695
## 225 -1.541693 0.10285079 0.064663422
## 226 -1.537715 0.10404145 0.065368971
## 227 -1.533737 0.10522648 0.066080366
## 228 -1.529759 0.10640535 0.066797630
## 229 -1.525781 0.10757890 0.067520786
## 230 -1.521803 0.10874619 0.068249857
## 231 -1.517825 0.10990315 0.068984867
## 232 -1.513848 0.11105286 0.069725837
## 233 -1.509870 0.11219505 0.070472791
## 234 -1.505892 0.11332508 0.071225749
## 235 -1.501914 0.11444428 0.071984734
## 236 -1.497936 0.11555407 0.072749767
## 237 -1.493958 0.11665230 0.073520869
## 238 -1.489980 0.11773450 0.074298061
## 239 -1.486002 0.11880547 0.075081364
## 240 -1.482024 0.11986497 0.075870798
## 241 -1.478046 0.12090552 0.076666383
## 242 -1.474068 0.12193154 0.077468138
## 243 -1.470090 0.12294439 0.078276083
## 244 -1.466112 0.12394024 0.079090237
## 245 -1.462134 0.12491558 0.079910619
## 246 -1.458156 0.12587618 0.080737246
## 247 -1.454178 0.12682184 0.081570137
## 248 -1.450200 0.12774211 0.082409310
## 249 -1.446222 0.12864537 0.083254782
## 250 -1.442244 0.12953231 0.084106570
## 251 -1.438267 0.13039716 0.084964691
## 252 -1.434289 0.13123857 0.085829160
## 253 -1.430311 0.13206249 0.086699994
## 254 -1.426333 0.13286846 0.087577208
## 255 -1.422355 0.13364418 0.088460818
## 256 -1.418377 0.13440144 0.089350837
## 257 -1.414399 0.13514016 0.090247281
## 258 -1.410421 0.13585256 0.091150163
## 259 -1.406443 0.13654031 0.092059496
## 260 -1.402465 0.13720882 0.092975295
## 261 -1.398487 0.13785625 0.093897571
## 262 -1.394509 0.13847242 0.094826338
## 263 -1.390531 0.13906892 0.095761606
## 264 -1.386553 0.13964572 0.096703387
## 265 -1.382575 0.14019341 0.097651692
## 266 -1.378597 0.14071696 0.098606532
## 267 -1.374619 0.14122069 0.099567917
## 268 -1.370641 0.14170138 0.100535857
## 269 -1.366663 0.14215191 0.101510360
## 270 -1.362686 0.14258280 0.102491435
## 271 -1.358708 0.14299407 0.103479091
## 272 -1.354730 0.14337526 0.104473335
## 273 -1.350752 0.14373440 0.105474175
## 274 -1.346774 0.14407442 0.106481618
## 275 -1.342796 0.14439097 0.107495669
## 276 -1.338818 0.14468039 0.108516335
## 277 -1.334840 0.14495144 0.109543620
## 278 -1.330862 0.14520423 0.110577530
## 279 -1.326884 0.14542810 0.111618070
## 280 -1.322906 0.14563332 0.112665241
## 281 -1.318928 0.14582134 0.113719049
## 282 -1.314950 0.14598725 0.114779495
## 283 -1.310972 0.14613063 0.115846582
## 284 -1.306994 0.14625811 0.116920312
## 285 -1.303016 0.14636985 0.118000685
## 286 -1.299038 0.14645614 0.119087702
## 287 -1.295060 0.14652805 0.120181363
## 288 -1.291083 0.14658580 0.121281667
## 289 -1.287105 0.14662467 0.122388614
## 290 -1.283127 0.14664668 0.123502201
## 291 -1.279149 0.14665629 0.124622426
## 292 -1.275171 0.14665291 0.125749287
## 293 -1.271193 0.14663131 0.126882779
## 294 -1.267215 0.14659924 0.128022899
## 295 -1.263237 0.14655696 0.129169642
## 296 -1.259259 0.14650080 0.130323004
## 297 -1.255281 0.14643399 0.131482977
## 298 -1.251303 0.14635906 0.132649555
## 299 -1.247325 0.14627529 0.133822732
## 300 -1.243347 0.14618109 0.135002500
## 301 -1.239369 0.14608095 0.136188850
## 302 -1.235391 0.14597518 0.137381773
## 303 -1.231413 0.14586201 0.138581260
## 304 -1.227435 0.14574438 0.139787301
## 305 -1.223457 0.14562337 0.140999884
## 306 -1.219479 0.14549887 0.142218998
## 307 -1.215502 0.14537161 0.143444632
## 308 -1.211524 0.14524325 0.144676771
## 309 -1.207546 0.14511410 0.145915403
## 310 -1.203568 0.14498512 0.147160513
## 311 -1.199590 0.14485732 0.148412087
## 312 -1.195612 0.14473099 0.149670108
## 313 -1.191634 0.14460733 0.150934562
## 314 -1.187656 0.14448789 0.152205431
## 315 -1.183678 0.14437214 0.153482697
## 316 -1.179700 0.14426037 0.154766342
## 317 -1.175722 0.14415682 0.156056348
## 318 -1.171744 0.14405917 0.157352694
## 319 -1.167766 0.14396763 0.158655361
## 320 -1.163788 0.14388525 0.159964327
## 321 -1.159810 0.14381290 0.161279570
## 322 -1.155832 0.14374865 0.162601069
## 323 -1.151854 0.14369331 0.163928800
## 324 -1.147876 0.14365302 0.165262739
## 325 -1.143898 0.14362270 0.166602861
## 326 -1.139921 0.14360257 0.167949142
## 327 -1.135943 0.14359794 0.169301555
## 328 -1.131965 0.14360766 0.170660073
## 329 -1.127987 0.14362922 0.172024670
## 330 -1.124009 0.14366454 0.173395316
## 331 -1.120031 0.14371981 0.174771983
## 332 -1.116053 0.14378839 0.176154641
## 333 -1.112075 0.14387047 0.177543259
##  [ reached 'max' / getOption("max.print") -- omitted 691 rows ]
## 
## $NCV
##            x             y
## 1   37.20461  4.117135e-01
## 2   37.20461  4.393335e-01
## 3   37.20461  1.087061e+00
## 4   37.20461  4.870608e-01
## 5   37.20461  5.271649e-01
## 6   37.20461  5.721798e-01
## 7   37.20461  5.905330e-01
## 8   37.20461  6.912274e-01
## 9   37.20461 -6.212726e-01
## 10  37.20461 -2.254392e-01
## 11  37.20461 -1.462726e-01
## 12  37.20461 -1.134601e-01
## 13  37.20461  5.245608e-01
## 14  37.20461  6.078941e-01
## 15  37.20461  4.273385e-01
## 16  37.20461  1.162274e-01
## 17  38.23965 -1.938197e-01
## 18  38.23965 -6.875697e-01
## 19  38.23965 -1.037570e+00
## 20  38.23965  7.186803e-01
## 21  38.23965 -2.431252e-01
## 22  38.23965  4.159699e-02
## 23  38.23965  7.603470e-01
## 24  38.23965  2.811803e-01
## 25  38.23965 -3.259625e-01
## 26  38.23965 -1.326774e+00
## 27  39.06764 -6.405541e-01
## 28  39.06764 -1.471046e+00
## 29  39.06764 -7.395124e-01
## 30  39.06764 -3.593041e-01
## 31  38.20904  1.294990e-01
## 32  38.20904  2.024157e-01
## 33  38.20904  2.805407e-01
## 34  38.20904 -5.757093e-01
## 35  38.20904 -1.465427e-01
## 36  38.20904 -1.369459e+00
## 37  38.20904 -5.840427e-01
## 38  38.20904 -2.819593e-01
## 39  38.20904 -1.673760e-01
## 40  38.41408  4.165305e-02
## 41  38.41408  9.187627e-02
## 42  38.41408  1.085924e+00
## 43  38.41408  1.380072e-01
## 44  38.41408  1.817572e-01
## 45  38.41408  2.213406e-01
## 46  38.41408  2.838406e-01
## 47  38.41408 -1.148337e-01
## 48  38.41408 -4.949278e-02
## 49  38.41408  8.150906e-01
## 50  38.41408  1.192572e-01
## 51  38.41408 -1.682428e-01
## 52  38.41408  1.900906e-01
## 53  38.41408  2.873128e-01
## 54  37.42623  6.570989e-01
## 55  37.42623  9.487656e-01
## 56  37.42623  8.307101e-01
## 57  37.42623  6.084878e-01
## 58  37.42623  3.832894e-01
## 59  37.42623  1.469599e+00
## 60  37.42623  4.737656e-01
## 61  36.45743 -2.855571e-01
## 62  36.45743 -1.553488e-01
## 63  36.45743 -1.980159e+00
## 64  36.45743 -6.588210e-01
## 65  36.45743 -1.332432e+00
## 66  37.48529  1.126276e-01
## 67  37.48529 -1.727890e-01
## 68  37.48529  9.730443e-01
## 69  37.48529  3.862387e-01
## 70  37.48529  2.890165e-01
## 71  37.48529 -2.509140e-01
## 72  37.48529  6.100727e-02
## 73  37.48529  7.751276e-01
## 74  37.48529  8.480443e-01
## 75  37.48529 -1.665390e-01
## 76  37.43831 -8.732037e-01
## 77  37.43831 -9.108568e-02
## 78  37.43831  8.950254e-01
## 79  37.54070  8.938212e-01
## 80  37.54070  9.974918e-01
## 81  37.54070  5.030474e-01
## 82  37.37467 -4.133666e-02
## 83  37.00493  5.757023e-02
## 84  37.37606 -2.232825e-01
## 85  37.37606 -1.015941e+00
## 86  37.37606 -1.546515e+00
## 87  37.37606 -9.302270e-01
## 88  34.98831  1.636687e+00
## 89  34.98831  4.214088e-01
## 90  36.05428  4.300939e-01
## 91  36.05428  7.790523e-01
## 92  36.05428 -9.823114e-01
## 93  36.05428  5.568300e-01
## 94  36.05428  6.040523e-01
## 95  36.05428 -2.432753e+00
## 96  36.05428  1.091552e+00
## 97  36.05428  4.526634e-01
## 98  36.05428  6.644689e-01
## 99  36.05428  3.540523e-01
## 100 36.05428 -1.420601e+00
## 101 36.05428  7.373856e-01
## 102 36.05428 -2.451918e-02
## 103 36.05428 -3.289023e-01
## 104 36.05428 -2.501144e-01
## 105 37.20849 -1.812659e+00
## 106 37.20849 -1.500159e+00
## 107 37.07192  8.197420e-01
## 108 37.07192  1.490575e+00
## 109 37.07192  8.989087e-01
## 110 37.07192  6.103670e-01
## 111 37.07192  1.240575e+00
## 112 37.07192  5.009920e-01
## 113 37.07192  9.558532e-01
## 114 37.45015 -2.626465e-01
## 115 37.45015 -1.758410e-01
## 116 37.45015  1.466520e+00
## 117 37.45015 -3.720215e-01
## 118 37.45015  4.568679e-02
## 119 37.45015 -5.980632e-01
## 120 37.45015  6.540201e-01
## 121 37.45015  1.071451e-01
## 122 37.45015 -7.812273e-02
## 123 37.45015 -5.702096e-03
## 124 37.45015  2.373535e-01
## 125 37.53963  1.895355e-01
## 126 37.53963 -3.271312e-01
## 127 37.53963 -1.785201e-01
## 128 37.53963 -9.171453e-02
## 129 37.53963 -8.458812e-01
## 130 37.53963 -1.237548e+00
## 131 37.53963 -7.661937e-01
## 132 37.53963 -1.277131e+00
## 133 37.53963 -2.479645e-01
## 134 37.53963 -1.420313e+00
## 135 37.53963  2.624521e-01
## 136 37.53963  3.353688e-01
## 137 37.53963 -3.896312e-01
## 138 37.53963 -5.842741e-01
## 139 37.53963 -4.483953e-02
## 140 37.53963 -2.315673e+00
## 141 37.93953  6.271322e-01
## 142 37.93953  7.714030e-01
## 143 37.93953  1.195882e+00
## 144 37.93953  9.479655e-01
## 145 37.93953  4.854655e-01
## 146 37.93953  7.598703e-01
## 147 37.93953  5.865072e-01
## 148 36.69657 -2.769279e-01
## 149 36.69657 -1.896263e-01
## 150 36.69657 -1.268540e+00
## 151 34.75347 -6.985463e-01
## 152 34.75347 -2.511557e-01
## 153 34.75347  9.550288e-03
## 154 34.75347  7.391041e-02
## 155 34.75347  6.059045e-01
## 156 36.03326 -5.931533e-01
## 157 36.03326 -2.124241e-01
## 158 36.03326 -1.113825e-01
## 159 35.11304 -4.922109e-01
## 160 37.05557 -9.156915e-01
## 161 35.77579 -1.305547e+00
## 162 37.05557 -8.125169e-01
## 163 37.05557 -1.293072e+00
## 164 37.05557 -7.639058e-01
## 165 37.68333 -9.114237e-15
## 166 37.21343  2.142248e-02
## 167 37.21343  5.834490e-01
## 168 37.21343  7.657407e-01
## 169 37.21343  1.268518e-01
## 170 37.21343  2.009258e-01
## 171 37.21343 -3.089121e-01
## 172 37.21343  5.240740e-01
## 173 36.78676 -5.284303e-01
## 174 36.78676  5.674030e-01
## 175 36.78676  8.302801e-02
## 176 36.78676  3.104586e-01
## 
## $HOMOGENEITY
##            x          y
## 1   37.20461 0.73632675
## 2   37.20461 0.76062424
## 3   37.20461 1.19646478
## 4   37.20461 0.80087471
## 5   37.20461 0.83319425
## 6   37.20461 0.86803907
## 7   37.20461 0.88185075
## 8   37.20461 0.95407714
## 9   37.20461 0.90451152
## 10  37.20461 0.54486357
## 11  37.20461 0.43888877
## 12  37.20461 0.38654010
## 13  37.20461 0.83113373
## 14  37.20461 0.89471964
## 15  37.20461 0.75016887
## 16  37.20461 0.39122564
## 17  38.23965 0.50680345
## 18  38.23965 0.95455068
## 19  38.23965 1.17259833
## 20  38.23965 0.97590718
## 21  38.23965 0.56761734
## 22  38.23965 0.23478568
## 23  38.23965 1.00379852
## 24  38.23965 0.61042611
## 25  38.23965 0.65724074
## 26  38.23965 1.32598664
## 27  39.06764 0.92652782
## 28  39.06764 1.40408620
## 29  39.06764 0.99552759
## 30  39.06764 0.69392356
## 31  38.20904 0.41558596
## 32  38.20904 0.51957678
## 33  38.20904 0.61168184
## 34  38.20904 0.87625261
## 35  38.20904 0.44208904
## 36  38.20904 1.35145708
## 37  38.20904 0.88257166
## 38  38.20904 0.61322653
## 39  38.20904 0.47247006
## 40  38.41408 0.23504760
## 41  38.41408 0.34908733
## 42  38.41408 1.20014054
## 43  38.41408 0.42784190
## 44  38.41408 0.49099633
## 45  38.41408 0.54182982
## 46  38.41408 0.61357779
## 47  38.41408 0.39027171
## 48  38.41408 0.25621429
## 49  38.41408 1.03976535
## 50  38.41408 0.39771754
## 51  38.41408 0.47238993
## 52  38.41408 0.50212596
## 53  38.41408 0.61731933
## 54  37.42623 0.93236997
## 55  37.42623 1.12034649
## 56  37.42623 1.04832906
## 57  37.42623 0.89721978
## 58  37.42623 0.71209233
## 59  37.42623 1.39435162
## 60  37.42623 0.79168909
## 61  36.45743 0.61814752
## 62  36.45743 0.45593145
## 63  36.45743 1.62778006
## 64  36.45743 0.93892167
## 65  36.45743 1.33526724
## 66  37.48529 0.38554219
## 67  37.48529 0.47753753
## 68  37.48529 1.13322391
## 69  37.48529 0.71396569
## 70  37.48529 0.61760494
## 71  37.48529 0.57545570
## 72  37.48529 0.28375283
## 73  37.48529 1.01143047
## 74  37.48529 1.05793429
## 75  37.48529 0.46882141
## 76  37.43831 1.07219781
## 77  37.43831 0.34629177
## 78  37.43831 1.08551246
## 79  37.54070 1.08578459
## 80  37.54070 1.14702537
## 81  37.54070 0.81455946
## 82  37.37467 0.23347404
## 83  37.00493 0.27581351
## 84  37.37606 0.54263027
## 85  37.37606 1.15747321
## 86  37.37606 1.42808381
## 87  37.37606 1.10756982
## 88  34.98831 1.53340768
## 89  34.98831 0.77808431
## 90  36.05428 0.76203474
## 91  36.05428 1.02559623
## 92  36.05428 1.15164257
## 93  36.05428 0.86707057
## 94  36.05428 0.90308863
## 95  36.05428 1.81235036
## 96  36.05428 1.21399078
## 97  36.05428 0.78177323
## 98  36.05428 0.94717550
## 99  36.05428 0.69139590
## 100 36.05428 1.38493410
## 101 36.05428 0.99779298
## 102 36.05428 0.18194749
## 103 36.05428 0.66638709
## 104 36.05428 0.58111553
## 105 37.20849 1.55205619
## 106 37.20849 1.41194585
## 107 37.07192 1.04212293
## 108 37.07192 1.40526205
## 109 37.07192 1.09128489
## 110 37.07192 0.89924056
## 111 37.07192 1.28201151
## 112 37.07192 0.81469633
## 113 37.07192 1.12531974
## 114 37.45015 0.58891191
## 115 37.45015 0.48186407
## 116 37.45015 1.39158105
## 117 37.45015 0.70088786
## 118 37.45015 0.24561779
## 119 37.45015 0.88866492
## 120 37.45015 0.92930880
## 121 37.45015 0.37614102
## 122 37.45015 0.32118348
## 123 37.45015 0.08677243
## 124 37.45015 0.55983787
## 125 37.53963 0.50131739
## 126 37.53963 0.65861028
## 127 37.53963 0.48653162
## 128 37.53963 0.34872782
## 129 37.53963 1.05906401
## 130 37.53963 1.28099822
## 131 37.53963 1.00794495
## 132 37.53963 1.30132353
## 133 37.53963 0.57340610
## 134 37.53963 1.37233316
## 135 37.53963 0.58991927
## 136 37.53963 0.66685107
## 137 37.53963 0.71877735
## 138 37.53963 0.88018877
## 139 37.53963 0.24383613
## 140 37.53963 1.75229059
## 141 37.93953 0.91137852
## 142 37.93953 1.01078761
## 143 37.93953 1.25852961
## 144 37.93953 1.12050942
## 145 37.93953 0.80185980
## 146 37.93953 1.00320335
## 147 37.93953 0.88136523
## 148 36.69657 0.60631898
## 149 36.69657 0.50172656
## 150 36.69657 1.29768711
## 151 34.75347 0.98780976
## 152 34.75347 0.59230754
## 153 34.75347 0.11550052
## 154 34.75347 0.32131316
## 155 34.75347 0.91997873
## 156 36.03326 0.89200673
## 157 36.03326 0.53380986
## 158 36.03326 0.38653880
## 159 35.11304 0.82921471
## 160 37.05557 1.10145538
## 161 35.77579 1.35353500
## 162 37.05557 1.03754877
## 163 37.05557 1.30889179
## 164 37.05557 1.00603298
## 165 37.68333        NaN
## 166 37.21343 0.16844952
## 167 37.21343 0.87909610
## 168 37.21343 1.00710734
## 169 37.21343 0.40990496
## 170 37.21343 0.51588489
## 171 37.21343 0.63966469
## 172 37.21343 0.83316537
## 173 36.78676 0.84127597
## 174 36.78676 0.87174694
## 175 36.78676 0.33347011
## 176 36.78676 0.64483178
## 
## $OUTLIERS
## OK: No outliers detected.
## - Based on the following method and threshold: cook (0.842).
## - For variable: (Whole model)
## 
## 
## $INFLUENTIAL
##             Hat Cooks_Distance Predicted    Residuals Std_Residuals Index Influential
## 1   0.007495498   3.699977e-04  37.20461  0.411713533   0.542177090     1          OK
## 2   0.007495498   4.213058e-04  37.20461  0.439333482   0.578549234     2          OK
## 3   0.007495498   2.579386e-03  37.20461  1.087060755   1.431527967     3          OK
## 4   0.007495498   5.178155e-04  37.20461  0.487060755   0.641400298     4          OK
## 5   0.007495498   6.065991e-04  37.20461  0.527164922   0.694212651     5          OK
## 6   0.007495498   7.146178e-04  37.20461  0.572179803   0.753491823     6          OK
## 7   0.007495498   7.611971e-04  37.20461  0.590532977   0.777660741     7          OK
## 8   0.007495498   1.042919e-03  37.20461  0.691227422   0.910263186     8          OK
## 9   0.007495498   8.425063e-04  37.20461 -0.621272578  -0.818141090     9          OK
## 10  0.007495498   1.109348e-04  37.20461 -0.225439245  -0.296876309    10          OK
## 11  0.007495498   4.670191e-05  37.20461 -0.146272578  -0.192623352    11          OK
## 12  0.007495498   2.809926e-05  37.20461 -0.113460078  -0.149413245    12          OK
## 13  0.007495498   6.006208e-04  37.20461  0.524560755   0.690783278    13          OK
## 14  0.007495498   8.066119e-04  37.20461  0.607894088   0.800523232    14          OK
## 15  0.007495498   3.986143e-04  37.20461  0.427338533   0.562753331    15          OK
## 16  0.007495498   2.948669e-05  37.20461  0.116227422   0.153057503    16          OK
## 17  0.019918979   2.234663e-04  38.23965 -0.193819674  -0.256849741    17          OK
## 18  0.019918979   2.812223e-03  38.23965 -0.687569674  -0.911167009    18          OK
## 19  0.019918979   6.403994e-03  38.23965 -1.037569674  -1.374986844    19          OK
## 20  0.019918979   3.072472e-03  38.23965  0.718680326   0.952394830    20          OK
## 21  0.019918979   3.516223e-04  38.23965 -0.243125230  -0.322189440    21          OK
## 22  0.019918979   1.029296e-05  38.23965  0.041596992   0.055124315    22          OK
## 23  0.019918979   3.439062e-03  38.23965  0.760346992   1.007611477    23          OK
## 24  0.019918979   4.703122e-04  38.23965  0.281180326   0.372620035    24          OK
## 25  0.019918979   6.320505e-04  38.23965 -0.325962531  -0.431965393    25          OK
## 26  0.019918979   1.047154e-02  38.23965 -1.326774220  -1.758240572    26          OK
## 27  0.041698375   5.344407e-03  39.06764 -0.640554051  -0.858453810    27          OK
## 28  0.041698375   2.818647e-02  39.06764 -1.471046475  -1.971458068    28          OK
## 29  0.041698375   7.123261e-03  39.06764 -0.739512384  -0.991075184    29          OK
## 30  0.041698375   1.681559e-03  39.06764 -0.359304051  -0.481529906    30          OK
## 31  0.032360064   1.662600e-04  38.20904  0.129498985   0.172711691    31          OK
## 32  0.032360064   4.062031e-04  38.20904  0.202415652   0.269960027    32          OK
## 33  0.032360064   7.802732e-04  38.20904  0.280540652   0.374154672    33          OK
## 34  0.032360064   3.285955e-03  38.20904 -0.575709348  -0.767818642    34          OK
## 35  0.032360064   2.129038e-04  38.20904 -0.146542681  -0.195442723    35          OK
## 36  0.032360064   1.859317e-02  38.20904 -1.369459348  -1.826436239    36          OK
## 37  0.032360064   3.381771e-03  38.20904 -0.584042681  -0.778932737    37          OK
## 38  0.032360064   7.881848e-04  38.20904 -0.281959348  -0.376046775    38          OK
## 39  0.032360064   2.777420e-04  38.20904 -0.167376015  -0.223227962    39          OK
## 40  0.021648581   1.125658e-05  38.41408  0.041653052   0.055247376    40          OK
## 41  0.021648581   5.476709e-05  38.41408  0.091876266   0.121861961    41          OK
## 42  0.021648581   7.650886e-03  38.41408  1.085923885   1.440337304    42          OK
## 43  0.021648581   1.235710e-04  38.41408  0.138007219   0.183048691    43          OK
## 44  0.021648581   2.143366e-04  38.41408  0.181757219   0.241077396    44          OK
## 45  0.021648581   3.178593e-04  38.41408  0.221340552   0.293579558    45          OK
## 46  0.021648581   5.227112e-04  38.41408  0.283840552   0.376477708    46          OK
## 47  0.021648581   8.555622e-05  38.41408 -0.114833690  -0.152312008    47          OK
## 48  0.021648581   1.589266e-05  38.41408 -0.049492781  -0.065645760    48          OK
## 49  0.021648581   4.310470e-03  38.41408  0.815090552   1.081111986    49          OK
## 50  0.021648581   9.227463e-05  38.41408  0.119257219   0.158179246    50          OK
## 51  0.021648581   1.836478e-04  38.41408 -0.168242781  -0.223152246    51          OK
## 52  0.021648581   2.344412e-04  38.41408  0.190090552   0.252130483    52          OK
## 53  0.021648581   5.355781e-04  38.41408  0.287312774   0.381083161    53          OK
## 54  0.016593757   2.125268e-03  37.42623  0.657098946   0.869313758    54          OK
## 55  0.016593757   4.430675e-03  37.42623  0.948765613   1.255176264    55          OK
## 56  0.016593757   3.396652e-03  37.42623  0.830710057   1.098993821    56          OK
## 57  0.016593757   1.822451e-03  37.42623  0.608487835   0.805003340    57          OK
## 58  0.016593757   7.231123e-04  37.42623  0.383289422   0.507075487    58          OK
## 59  0.016593757   1.063040e-02  37.42623  1.469598946   1.944216453    59          OK
## 60  0.016593757   1.104788e-03  37.42623  0.473765613   0.626771611    60          OK
## 61  0.038737683   9.806386e-04  36.45743 -0.285557093  -0.382106351    61          OK
## 62  0.038737683   2.902276e-04  36.45743 -0.155348760  -0.207873484    62          OK
## 63  0.038737683   4.715452e-02  36.45743 -1.980159366  -2.649667923    63          OK
## 64  0.038737683   5.219849e-03  36.45743 -0.658820982  -0.881573904    64          OK
## 65  0.038737683   2.135076e-02  36.45743 -1.332432093  -1.782938604    65          OK
## 66  0.011840999   4.412634e-05  37.48529  0.112627637   0.148642780    66          OK
## 67  0.011840999   1.038581e-04  37.48529 -0.172789030  -0.228042090    67          OK
## 68  0.011840999   3.293618e-03  37.48529  0.973044304   1.284196441    68          OK
## 69  0.011840999   5.189430e-04  37.48529  0.386238748   0.509747011    69          OK
## 70  0.011840999   2.905717e-04  37.48529  0.289016526   0.381435863    70          OK
## 71  0.011840999   2.190069e-04  37.48529 -0.250914030  -0.331149263    71          OK
## 72  0.011840999   1.294706e-05  37.48529  0.061007267   0.080515671    72          OK
## 73  0.011840999   2.090039e-03  37.48529  0.775127637   1.022991603    73          OK
## 74  0.011840999   2.501757e-03  37.48529  0.848044304   1.119224965    74          OK
## 75  0.011840999   9.648061e-05  37.48529 -0.166539030  -0.219793516    75          OK
## 76  0.006984488   1.549269e-03  37.43831 -0.873203735  -1.149608142    76          OK
## 77  0.006984488   1.685761e-05  37.43831 -0.091085680  -0.119917992    77          OK
## 78  0.006984488   1.627671e-03  37.43831  0.895025431   1.178337291    78          OK
## 79  0.010647368   2.492956e-03  37.54070  0.893821174   1.178928168    79          OK
## 80  0.010647368   3.104788e-03  37.54070  0.997491809   1.315667188    80          OK
## 81  0.010647368   7.896435e-04  37.54070  0.503047364   0.663507114    81          OK
## 82  0.010214968   5.110922e-06  37.37467 -0.041336661  -0.054510129    82          OK
## 83  0.014269208   1.396215e-05  37.00493  0.057570229   0.076073091    83          OK
## 84  0.010267274   1.499001e-04  37.37606 -0.223282528  -0.294447613    84          OK
## 85  0.010267274   3.103343e-03  37.37606 -1.015941258  -1.339744229    85          OK
## 86  0.010267274   7.191190e-03  37.37606 -1.546514851  -2.039423373    86          OK
## 87  0.010267274   2.601779e-03  37.37606 -0.930226972  -1.226710903    87          OK
## 88  0.166078816   1.835137e-01  34.98831  1.636686530   2.351339112    88          OK
## 89  0.166078816   1.216591e-02  34.98831  0.421408753   0.605415187    89          OK
## 90  0.055826006   3.323015e-03  36.05428  0.430093917   0.580696951    90          OK
## 91  0.055826006   1.090282e-02  36.05428  0.779052250   1.051847628    91          OK
## 92  0.055826006   1.733421e-02  36.05428 -0.982311386  -1.326280620    92          OK
## 93  0.055826006   5.569947e-03  36.05428  0.556830028   0.751811376    93          OK
## 94  0.055826006   6.554730e-03  36.05428  0.604052250   0.815569079    94          OK
## 95  0.055826006   1.063168e-01  36.05428 -2.432753305  -3.284613829    95          OK
## 96  0.055826006   2.140399e-02  36.05428  1.091552250   1.473773608    96          OK
## 97  0.055826006   3.680921e-03  36.05428  0.452663361   0.611169383    97          OK
## 98  0.055826006   7.931496e-03  36.05428  0.664468917   0.897141436    98          OK
## 99  0.055826006   2.251855e-03  36.05428  0.354052250   0.478028296    99          OK
## 100 0.055826006   3.625348e-02  36.05428 -1.420600528  -1.918042461   100          OK
## 101 0.055826006   9.767762e-03  36.05428  0.737385583   0.995590831   101          OK
## 102 0.055826006   1.079985e-05  36.05428 -0.024519178  -0.033104891   102          OK
## 103 0.055826006   1.943299e-03  36.05428 -0.328902295  -0.444071754   103          OK
## 104 0.055826006   1.123785e-03  36.05428 -0.250114417  -0.337695265   104          OK
## 105 0.025398181   2.520310e-02  37.20849 -1.812659472  -2.408878408   105          OK
## 106 0.025398181   1.726221e-02  37.20849 -1.500159472  -1.993591084   106          OK
## 107 0.019374605   3.883777e-03  37.07192  0.819742043   1.086020203   107          OK
## 108 0.019374605   1.284126e-02  37.07192  1.490575376   1.974761435   108          OK
## 109 0.019374605   4.670152e-03  37.07192  0.898908709   1.190902709   109          OK
## 110 0.019374605   2.153188e-03  37.07192  0.610367043   0.808633576   110          OK
## 111 0.019374605   8.895004e-03  37.07192  1.240575376   1.643553522   111          OK
## 112 0.019374605   1.450646e-03  37.07192  0.500992043   0.663730115   112          OK
## 113 0.019374605   5.280587e-03  37.07192  0.955853154   1.266344511   113          OK
## 114 0.012887725   2.617338e-04  37.45015 -0.262646541  -0.346817235   114          OK
## 115 0.012887725   1.173158e-04  37.45015 -0.175840985  -0.232192985   115          OK
## 116 0.012887725   8.160044e-03  37.45015  1.466520126   1.936497827   116          OK
## 117 0.012887725   5.251128e-04  37.45015 -0.372021541  -0.491243790   117          OK
## 118 0.012887725   7.919500e-06  37.45015  0.045686792   0.060328101   118          OK
## 119 0.012887725   1.357096e-03  37.45015 -0.598063208  -0.789725338   119          OK
## 120 0.012887725   1.622926e-03  37.45015  0.654020126   0.863614846   120          OK
## 121 0.012887725   4.355733e-05  37.45015  0.107145126   0.141482070   121          OK
## 122 0.012887725   2.315641e-05  37.45015 -0.078122731  -0.103158829   122          OK
## 123 0.012887725   1.233632e-07  37.45015 -0.005702096  -0.007529455   123          OK
## 124 0.012887725   2.137507e-04  37.45015  0.237353459   0.313418445   124          OK
## 125 0.021063713   2.265063e-04  37.53963  0.189535469   0.251319128   125          OK
## 126 0.021063713   6.747506e-04  37.53963 -0.327131197  -0.433767503   126          OK
## 127 0.021063713   2.009433e-04  37.53963 -0.178520086  -0.236713015   127          OK
## 128 0.021063713   5.303660e-05  37.53963 -0.091714531  -0.121611095   128          OK
## 129 0.021063713   4.511470e-03  37.53963 -0.845881197  -1.121616580   129          OK
## 130 0.021063713   9.656580e-03  37.53963 -1.237547864  -1.640956445   130          OK
## 131 0.021063713   3.701489e-03  37.53963 -0.766193697  -1.015953017   131          OK
## 132 0.021063713   1.028420e-02  37.53963 -1.277131197  -1.693442921   132          OK
## 133 0.021063713   3.876845e-04  37.53963 -0.247964531  -0.328794552   133          OK
## 134 0.021063713   1.271942e-02  37.53963 -1.420313016  -1.883298307   134          OK
## 135 0.021063713   4.343097e-04  37.53963  0.262452136   0.348004741   135          OK
## 136 0.021063713   7.091607e-04  37.53963  0.335368803   0.444690354   136          OK
## 137 0.021063713   9.572090e-04  37.53963 -0.389631197  -0.516640886   137          OK
## 138 0.021063713   2.152447e-03  37.53963 -0.584274055  -0.774732278   138          OK
## 139 0.021063713   1.267715e-05  37.53963 -0.044839531  -0.059456058   139          OK
## 140 0.021063713   3.381067e-02  37.53963 -2.315672864  -3.070522298   140          OK
## 141 0.018822483   2.205836e-03  37.93953  0.627132215   0.830610811   141          OK
## 142 0.018822483   3.337473e-03  37.93953  0.771403049   1.021691592   142          OK
##  [ reached 'max' / getOption("max.print") -- omitted 34 rows ]
## 
## $PP_CHECK

## 
## attr(,"class")
## [1] "check_model"     "see_check_model"
## attr(,"panel")
## [1] TRUE
## attr(,"dot_size")
## [1] 2
## attr(,"line_size")
## [1] 0.8
## attr(,"base_size")
## [1] 10
## attr(,"axis_title_size")
## [1] 10
## attr(,"title_size")
## [1] 12
## attr(,"check")
## [1] "all"
## attr(,"alpha")
## [1] 0.2
## attr(,"dot_alpha")
## [1] 0.8
## attr(,"show_dots")
## [1] TRUE
## attr(,"detrend")
## [1] TRUE
## attr(,"colors")
## [1] "#3aaf85" "#1b6ca8" "#cd201f"
## attr(,"theme")
## [1] "see::theme_lucid"
## attr(,"model_info")
## attr(,"model_info")$is_binomial
## [1] FALSE
## 
## attr(,"model_info")$is_bernoulli
## [1] FALSE
## 
## attr(,"model_info")$is_count
## [1] FALSE
## 
## attr(,"model_info")$is_poisson
## [1] FALSE
## 
## attr(,"model_info")$is_negbin
## [1] FALSE
## 
## attr(,"model_info")$is_beta
## [1] FALSE
## 
## attr(,"model_info")$is_betabinomial
## [1] FALSE
## 
## attr(,"model_info")$is_orderedbeta
## [1] FALSE
## 
## attr(,"model_info")$is_dirichlet
## [1] FALSE
## 
## attr(,"model_info")$is_exponential
## [1] FALSE
## 
## attr(,"model_info")$is_logit
## [1] FALSE
## 
## attr(,"model_info")$is_probit
## [1] FALSE
## 
## attr(,"model_info")$is_censored
## [1] FALSE
## 
## attr(,"model_info")$is_truncated
## [1] FALSE
## 
## attr(,"model_info")$is_survival
## [1] FALSE
## 
## attr(,"model_info")$is_linear
## [1] TRUE
## 
## attr(,"model_info")$is_tweedie
## [1] FALSE
## 
## attr(,"model_info")$is_zeroinf
## [1] FALSE
## 
## attr(,"model_info")$is_zero_inflated
## [1] FALSE
## 
## attr(,"model_info")$is_dispersion
## [1] FALSE
## 
## attr(,"model_info")$is_hurdle
## [1] FALSE
## 
## attr(,"model_info")$is_ordinal
## [1] FALSE
## 
## attr(,"model_info")$is_cumulative
## [1] FALSE
## 
## attr(,"model_info")$is_multinomial
## [1] FALSE
## 
## attr(,"model_info")$is_categorical
## [1] FALSE
## 
## attr(,"model_info")$is_mixed
## [1] FALSE
## 
## attr(,"model_info")$is_multivariate
## [1] FALSE
## 
## attr(,"model_info")$is_trial
## [1] FALSE
## 
## attr(,"model_info")$is_bayesian
## [1] FALSE
## 
## attr(,"model_info")$is_gam
## [1] FALSE
## 
## attr(,"model_info")$is_anova
## [1] FALSE
## 
## attr(,"model_info")$is_timeseries
## [1] FALSE
## 
## attr(,"model_info")$is_ttest
## [1] FALSE
## 
## attr(,"model_info")$is_correlation
## [1] FALSE
## 
## attr(,"model_info")$is_onewaytest
## [1] FALSE
## 
## attr(,"model_info")$is_chi2test
## [1] FALSE
## 
## attr(,"model_info")$is_ranktest
## [1] FALSE
## 
## attr(,"model_info")$is_levenetest
## [1] FALSE
## 
## attr(,"model_info")$is_variancetest
## [1] FALSE
## 
## attr(,"model_info")$is_xtab
## [1] FALSE
## 
## attr(,"model_info")$is_proptest
## [1] FALSE
## 
## attr(,"model_info")$is_binomtest
## [1] FALSE
## 
## attr(,"model_info")$is_ftest
## [1] FALSE
## 
## attr(,"model_info")$is_meta
## [1] FALSE
## 
## attr(,"model_info")$link_function
## [1] "identity"
## 
## attr(,"model_info")$family
## [1] "gaussian"
## 
## attr(,"model_info")$n_obs
## [1] 176
## 
## attr(,"model_info")$n_grouplevels
## NULL
## 
## attr(,"bandwidth")
## [1] "nrd"
## attr(,"type")
## [1] "density"
## attr(,"model_class")
## [1] "lm"

emmeans::emmeans(ctmax_temp.model, specs = "genus") %>% 
  data.frame() %>% 
  mutate(genus = fct_reorder(genus, .x = emmean, .desc = T)) %>% 
  ggplot(aes(genus, y = emmean)) + 
  geom_point(size = 4) + 
  geom_errorbar(aes(ymin = emmean - SE, ymax = emmean + SE), 
                width = 0.2, linewidth = 1) + 
  labs(x = "") + 
  theme_matt() + 
  theme(axis.text.x = element_text(angle = 300, hjust = 0, vjust = 0.5))

ctmax_data %>% 
  mutate(group_id = paste(site, species)) %>% 
  ggplot(aes(x = fecundity, y = site, fill = site)) + 
  geom_density_ridges(bandwidth = 2,
                      jittered_points = TRUE, 
                      point_shape = 21,
                      point_size = 1,
                      point_colour = "grey30",
                      point_alpha = 0.6,
                      alpha = 0.9,
                      position = position_points_jitter(
                        height = 0.1, width = 0)) + 
  scale_fill_viridis_d(option = "E", direction = -1) + 
  theme_matt() + 
  theme(legend.position = "none")

ctmax_data %>% 
  mutate(group_id = paste(site, species)) %>% 
  ggplot(aes(x = size, y = site, fill = site, group = group_id)) + 
  geom_density_ridges(bandwidth = 0.02,
                      jittered_points = TRUE, 
                      point_shape = 21,
                      point_size = 1,
                      point_colour = "grey30",
                      point_alpha = 0.6,
                      alpha = 0.9,
                      position = position_points_jitter(
                        height = 0.1, width = 0)) + 
  scale_fill_viridis_d(option = "E", direction = -1) + 
  theme_matt() + 
  theme(legend.position = "none")

ctmax_data %>% 
  mutate(group_id = paste(site, species)) %>% 
  ggplot(aes(x = ctmax, y = site, fill = site, group = group_id)) + 
  geom_density_ridges(bandwidth = 0.3,
                      jittered_points = TRUE, 
                      point_shape = 21,
                      point_size = 1,
                      point_colour = "grey30",
                      point_alpha = 0.6,
                      alpha = 0.9,
                      position = position_points_jitter(
                        height = 0.1, width = 0)) + 
  scale_fill_viridis_d(option = "E", direction = -1) + 
  labs(x = "CTmax (°C)") + 
  theme_matt() + 
  theme(legend.position = "none")